j
jadee_chen

Jade C.

@jadee_chen

Senior AI Engineer, Tech Lead: Optimization, AI Engineering, ML, DL Pipelines

Estados Unidos
Inglês, Chinês
Algumas informações são exibidas no idioma inglês.
Sobre mim
Senior Data Scientist & Tech Lead (6+ yrs) with an MS in Applied Math from UC Santa Cruz. I build production-grade AI systems, local LLM infrastructure, and supply chain models. SPECIALTIES: • Local LLM Ops: Private vLLM/Ollama setup (DeepSeek/Qwen), AI agents & RAG • Operations Research: Supply chain simulation (SimPy/Monte Carlo) & MILP • Production Apps: FastAPI REST APIs, Streamlit dashboards & Docker I turn complex requirements into clean, low-latency, scalable code. Message me to start!... Saiba mais

Habilidades

j
jadee_chen
Jade C.
offline • 

Conheça meus serviços

Painéis de dados
I will build interactive streamlit dashboards and production fastapi ml backends
A partir deUS$ 100 /projetoMais detalhes
Modelagem e Análise Estatística
I will do statistical analysis and python data science for business insights
A partir deUS$ 50 /projetoMais detalhes

Portfólio

Experiência profissional

Mindray

Senior Data Scientist & Tech Lead

Mindray • Período integral

May 2024 - Jun 2026 • 2 yrs 1 mo

• Established and grew the first Data Science & AI team for the IVD Supply Chain department from the ground up, introducing Agile workflows and technical roadmaps. • Architected production ML pipelines bridging legacy ERP systems with modern forecasting models to optimize enterprise-wide supply chain logistics. • Developed Streamlit-based monitoring interfaces for real-time model validation, tracking inventory drift and loss calculations for production reliability. • Mentored 2 fresh-graduate junior data scientists in machine learning modeling, code quality standards, and distribution center logistics optimization.

Medidata

Senior Data Scientist

Medidata • Período integral

Oct 2021 - Apr 2024 • 2 yrs 6 mos

• Led a cross-functional team to deploy Anomaly Detection models (Isolation Forest, LOF), replacing legacy statistical methods for clinical data quality control. • Optimized XGBoost/LightGBM enrollment models, integrating longitudinal data pipelines for clinical trial forecasting. • Deployed validation dashboards to track model variance, LLM hallucinations, and behavior drift in production environments.